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Neural network classifier for ship domain assessment

Author

Listed:
  • Lisowski, Józef
  • Rak, Andrzej
  • Czechowicz, Wojciech

Abstract

The article presents an attempt to apply an artificial neural network in anti-collision systems at sea. Such systems determine safe trajectory for a ship by, most frequently, processing the information sourced from an automatic radar plotting aids (ARPA) type arrangement. In this research work the use of neural classifier has been proposed as an element supporting a navigator in the process of determining the ship’s domain, i.e., the area around a ship which, for safety reasons, should remain free from navigational obstacles. Neural classifier has a form of a multilayer feed-forward network of a perceptronic nature. It has been assigned a task to represent the evaluation of a navigational situation provided by an experienced navigator functioning as a teacher in the process of the network learning phase. Programs designed in the MATLAB language have been applied for the simulation of the network and also for the illustration of a navigational situation. Testing of the correctness of classification of the collision situations by the network have been also conducted. In the final part of the article conclusions have been formulated with regard to the application of the neural classifier in the process of determining a safe trajectory of a ship.

Suggested Citation

  • Lisowski, Józef & Rak, Andrzej & Czechowicz, Wojciech, 2000. "Neural network classifier for ship domain assessment," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 51(3), pages 399-406.
    • Handle: RePEc:eee:matcom:v:51:y:2000:i:3:p:399-406
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